Vast amounts of data are being made accessible to users that may be processed by data flow pipelines to model the data, discover useful information, may suggest correspondence between different factors represented in the data, and so on. These techniques are commonly referred to as data analytics, “big data,” data mining, and so forth.
Conventional techniques to design and implement data flow pipelines, however, required specialized knowledge of highly-trained technicians. Further, these conventional techniques may involve a significant amount of time to perform even by a technician having this specialized knowledge, which may be due to the complexity both in designing a data flow pipeline that may be functional as well as provisioning the data flow pipeline for actual implementation. Thus, these conventional techniques could hinder user access to this functionality, both in the knowledge needed to design the data flow pipeline as well as the time required to do so.